Research on filter-based adversarial feature selection against evasion attacks by Qimeng HUANG, Miaomiao WU, Yun LI

“…With the rapid development and widespread application of machine learning technology, its security has attracted increasing attention, leading to a growing interest in adversarial machine learning.In adversarial scenarios, machine learning techniques are threatened by attacks that manipulate a small number of samples to induce misclassification, resulting in serious consequences in various domains such as spam detection, traffic signal recognition, and network intrusion detection.An evaluation criterion for filter-based adversarial feature selection was proposed, based on the minimum redundancy and maximum relevance (mRMR) method, while considering security metrics against evasion attacks.Additionally, a robust adversarial feature selection algorithm was introduced, named SDPOSS, which was based on the decomposition-based Pareto optimization for subset selection (DPOSS) algorithm.SDPOSS didn’t depend on subsequent models and effectively handles large-scale high-dimensional feature spaces.Experimental results demonstrate that as the number of decompositions increases, the runtime of SDPOSS decreases linearly, while achieving excellent classification performance.Moreover, SDPOSS exhibits strong robustness against evasion attacks, providing new insights for adversarial machine learning.…”
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Three-Dimensional Extended Target Tracking and Shape Learning Based on Double Fourier Series and Expectation Maximization by Hongge Mao, Xiaojun Yang

“…Specifically, the 3D shape is modeled using a radial function estimated via double Fourier series (DFS) expansion, and orientation is represented using the compact, singularity-free axis-angle method. The ECM algorithm facilitates this joint estimation: an Unscented Kalman Smoother infers kinematics in the E-step, while the M-step estimates DFS shape parameters and rotation angles by minimizing regularized cost functions, promoting robustness and smoothness. …”
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A novel framework for optimizing residential load response planning with consideration of user satisfaction by Mohammad Hossein Erfani Majd, Gholam-Reza Kamyab, Saeed Balochian

“…The proposed method utilizes the Meerkat Optimization Algorithm (MOA), which is compared against other optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Teaching-Learning-Based Optimization (TLBO). …”
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Continued Fraction Interpolation of Preserving Horizontal Asymptote by Yushan Zhao, Kaiwen Wu, Jieqing Tan

“…By means of the relationship between the leading coefficients of the numerator and the denominator and the reciprocal differences of the continued fraction interpolation, a novel algorithm for the continued fraction interpolation is constructed in an effort to preserve the horizontal asymptote while approximating the given function with a horizontal asymptote. …”
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Optimization of Processor Clock Frequency for Sensor Network Nodes Based on Energy Use and Timing Constraints by Youngmin Kim, Heeju Joo, Chan-Gun Lee

“…We analyze the extended model and verify that our algorithm calculates the clock frequency that optimizes energy savings while satisfying the timing constraints.…”
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Research on large-scale identity authentication architecture based on combined symmetric key by LIU Tong, XU Guan-ning

“…A large-scale real-name authentication architecture and key management protocol based on combined symmet-ric key algorithm were proposed.With the CSK algorithm and smart card technology, the authentication process can be finished in the chips, and the management of large-scale keys can be simplified to the management of small-scale key seeds.The security of the proposed architecture is analyzed and the experimental results are shown.It is obvious that the abilities of large-scale identity authentication and management are improved while the building cost is reduced evidently with the application of the proposed architecture.It is an applicable solution for real-name authentication network.…”
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Research on range matching for wire-speed hardware NIDS by CHEN Shu-hui, SUN Zhi-gang, SU Jin-shu

“…To solve the rule matching problem of hardware NIDS,a range matching algorithm LRC-RM was proposed,with more efficient memory utilization.The approach mapped the port range into a compressed bit vector and organized the bit vectors as an extended balanced binary tree.Experiments were employed to show that NIDS using this approach can perform wire-speed range matching for OC-192 links,while saving 99% memory resource comparing to the existing methods.The algorithm is easy to be implemented within a chip without additional RAM.…”
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Deadline-Aware Energy-Efficient Query Scheduling in Wireless Sensor Networks with Mobile Sink by Murat Karakaya

“…Thus, the proposed scheduling algorithm aims to minimize the number of missed deadlines while keeping the level of energy consumption at the minimum.…”
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Reconstruction of linear block code parity-check matrix based on fault-tolerant Gaussian elimination by WANG Zhongyong, ZHANG Hong, GONG Kexian, WANG Wei, ZHANG Ling, ZHU Junhao

“…For the LDPC(648,324) code under the IEEE802.11n protocol, the existing algorithms fail when the bit error rate reaches 0.005 5, while the reconstruction rate of the proposed algorithm for the parity-check matrix still reaches over 98% when the bit error rate is 0.008.…”
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Optimal fusion β-quaternion filtering from delayed observations and packet losses with compensation strategy under properness by J. D. Jiménez-López, R. M. Fernández-Alcalá, F. Gutiérrez-Trujillo, E. Grassucci, D. Comminiello

“…Under first-order properness conditions, a recursive algorithm is developed to compute the optimal filter. …”
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A Time- and Space-Integrated Expansion Planning Method for AC/DC Hybrid Distribution Networks by Yao Guo, Shaorong Wang, Dezhi Chen

“…The simulation results show that the modified algorithm outperforms traditional algorithm in terms of both training efficiency and stability, with a faster convergence and lower fluctuation in cumulative rewards. …”
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Lightweight Vehicle Detection Based on Mamba_ViT by Ze Song, Yuhai Wang, Shuobo Xu, Peng Wang, Lele Liu

“…Additionally, a multi-scale feature fusion mechanism is employed to enhance the integration of shallow and deep features, leading to the development of a vehicle detection algorithm named Mamba_ViT_YOLO. The experimental results on the UA-DETRAC dataset show that our proposed algorithm improves mAP@50 by 3.2% compared to the latest YOLOv8 algorithm, while using only 60% of the model parameters.…”
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OPTIMAL DISTRIBUTION NETWORK RECONFIGURATION FOR LOSS MINIMIZATION AND VOLTAGE PROFILE IMPROVEMENT BASED ON ARTIFICIAL INTELLIGENCE by Omar Muhammed Neda

“…As the reconfiguration problem is a discrete issue, the original DEO algorithm cannot deal with this problem. Fortunately, a Binary DEO (BDEO) algorithm was presented for solving discrete optimization issues which is utilized for adapting the reconfiguration issue. …”
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A global object-oriented dynamic network for low-altitude remote sensing object detection by Daoze Tang, Shuyun Tang, Yalin Wang, Shaoyun Guan, Yining Jin

“…However, achieving high accuracy with deep learning algorithms remains challenging due to the stringent requirements for low computational cost, minimal parameters, and real-time performance. …”
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Pickup and delivery problem solver for multiple mobile robots considering robot’s dynamics by Tomoaki Shimizu, Ayumu Goto, Kosuke Taneda, Takeshi Muranaka, Yuji Enoki, Toyokazu Kobayashi, Tomoya Hattori, Ryota Takamido, Jun Ota

“…Using the proposed algorithm, we obtained superior solutions with makespans of 34–58% shorter than those of the existing methods, while maintaining manageable computation time, even in complex scenarios involving many robots and obstacles. …”
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Utilizing weak graph for edge consolidation-based efficient enhancement of network robustness by Wei Ding, Zhengdan Wang

“…We compare the proposed algorithm with optimal and approximate algorithms across graphs of varying scales. …”
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Research on bearing fault feature transfer diagnosis based on balanced distribution adaptation under feature fusion by Lulu Wang, Yongqi Li, Chunyi Zhang, Ralph Gerard Sangalang

“…Principal Component Analysis (PCA) is then utilized to reduce the dimensionality of the high-dimensional features, preserving the main information while reducing computational complexity. Subsequently, the BDA algorithm is employed to align the features of the source and target domains, balancing distribution differences and achieving effective feature space transfer. …”
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Estimating the Compressive Strength of Cement-Based Materials with Mining Waste Using Support Vector Machine, Decision Tree, and Random Forest Models by Hongxia Ma, Jiandong Liu, Jia Zhang, Jiandong Huang

“…The SVM model can obtain the minimum RMSE, while the BAS algorithm is inefficient in DT and RF models. …”
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Zynq FPGA-Based Acceleration of Kernelized Correlation Filters via High-Level Synthesis of a Custom DFT Block by Enver Çavuş, Mustafa Yetiş

“…This study presents a hardware-software co-design implementation of an accelerator for the Kernelized Correlation Filter (KCF) tracking algorithm. Leveraging the High-level synthesis (HLS) and the Zynq heterogeneous platform, the KCF algorithm’s performance is enhanced by using a custom hardware implementation for the computationally intensive Discrete Fourier Transform (DFT) operation. …”
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Local Search-Based Metaheuristic Methods for the Solid Waste Collection Problem by Haneen Algethami

“…Hence, it is necessary to find feasible routes while minimising operational costs and fuel consumption. …”
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